Introduction to Natural Language Processing
Logistics
When: Tuesday and Thursday, 11:00 am-12:15 pm ET
Where: 011 Sitterson Hall
TA Office hours: 12:30-1:30 Tues (FB 241B)
Instructor Office hours: 12:15 -1:15 Thu (email for appt)
Sign up on the course Piazza (Access code is comp590)
Announcements:
Jan 24: Assignment 1 is out (due on Feb 14)
Jan 31: Some suggested project ideas here
Feb 16: Assignment 2 is out (due on March 9 )
Mar 21: Assignment 3 is out (due on April 9)
April 11: Assignment 4 is out (due on April 30)
People
Course Information
Natural Language Processing (NLP) is about making human languages accessible to computers. In the past couple of decades, the availability of larger datasets and advances in machine learning and high-performance systems have led to unprecedented advances in NLP. Today, NLP systems have become ubiquitous in everyday lives: including Machine Translation systems on the web, text classification systems for automatically categorizing emails, and automatic speech recognition systems to name a few. This course will cover the foundations of algorithms, representations and machine learning methods for NLP, as well as sample some major applications and areas of active research. The tentative list of topics is:
Text Representation
Review of probability & optimization
Text Classification
Tagging, Named Entity Recognition, Coreference resolution
Syntactic & Semantic Parsing, Machine Translation
Language Modeling: n-gram models, Markov models, Transformers
Social Aspects of NLP
The course will be at an advanced undergraduate/beginner graduate level, and will presume a functional understanding of Machine Learning, Probability, Statistics and Linear algebra. The assignments and project will have substantial programming components.
